Operations Quality Engineering Lead

At Bedrock were moving AI out of the lab and into the real world. Our team includes veterans who helped launch Waymo scaled Segment to a $3.2B acquisition and grew Uber Freight to $5B in revenue. Today were deploying autonomous systems on heavy construction equipment across the country improving safety on job sites and accelerating schedules on critical infrastructure projects.

Were not here debating the future of AI. Were deploying it in the real just two years weve raised $350M and achieved the first fully autonomous excavator deployments in construction.

This is where algorithms meet steel-toed boots. Youll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations cant touch. If youre ready to do meaningful work on hard problems wed love to have you join us.

Role Overview:

We are seeking a Product Quality Engineer to establish and drive end-to-end quality strategy across hardware development and robotic fleet operations. This role sits at the intersection of engineering manufacturing and field operations ensuring product reliability scalability and performance from early prototyping through high-volume production and real-world deployment.

You will own quality systems metrics and continuous improvement initiatives across the full lifecyclespanning design supplier quality manufacturing execution and field performancewhile leveraging modern tools including automation diagnostics and AI-driven workflows.

Product & Design Quality

• Lead Design for Quality initiatives including Design for Manufacturing (DFM) and Design for Assembly (DFA)

• Partner with hardware electrical and software engineering teams during EVT/DVT/PVT phases to ensure robust design validation

• Define and enforce quality gates risk assessments (FMEA) and validation plans

• Drive design improvements based on failure data field insights and reliability testing

• Risk Management: Proactively identify and mitigate business-critical risks and dependencies that may impact delivery or operational performance. Develop contingency plans as necessary and maintain visibility to the relevant company functions of major issues and alerts.

Manufacturing & Supplier Quality

• Establish and manage Incoming Quality Control (IQC) In-Process Quality Control (IPQC) and Outgoing Quality Control (OQC) frameworks

• Develop supplier quality strategy including qualification audits and performance management

• Implement process controls yield tracking and defect reduction initiatives across contract manufacturers

• Lead root cause analysis and corrective/preventative actions (CAPA) for production issues

Reliability & Validation

• Define reliability requirements and test strategies (HALT/HASS environmental lifecycle testing)

• Own validation metrics and ensure products meet performance and durability targets

• Drive continuous reliability improvements through structured failure analysis

Fleet Quality & Field Operations

• Establish systems for field triage failure tracking and escalation management across deployed robotic fleets

• Analyze field performance data to identify systemic issues and prioritize fixes

• Partner with operations and service teams to improve uptime serviceability and MTBF

• Develop feedback loops from field engineering manufacturing

Software & Systems Quality

• Ensure alignment between hardware and software quality standards

• Define test strategies for embedded systems firmware and cloud-connected platforms

• Drive automated testing frameworks (HIL/SIL) regression testing and release quality metrics

Data Metrics & Continuous Improvement

• Define and track KPIs across the lifecycle: yield defect rates DPPM MTBF MTTR fleet uptime

• Build dashboards and reporting systems to provide visibility across engineering operations and leadership

• Lead structured problem-solving using 8D 5 Whys Fishbone and statistical methods

Automation Diagnostics & AI Enablement

• Build diagnostic and alert frameworks for rapid issue identification and communication across hardware and software systems

• Leverage AI agents and tools to:

  • Streamline root cause analysis and data triage

  • Automate reporting anomaly detection and workflow management

  • Improve cross-functional coordination across complex multi-phase programs

• Experience: 8-10 years in quality program management or a similar role with proven experience managing complex cross-functional projects in fast-paced tech-driven environments.

• Technical Proficiency: Strong understanding of quality concepts and the ability to communicate complex ideas across diverse teams. Experience with robotics automation or key hardware-related areas such as compute memory design and utilization is a plus.

• Problem-Solving Mindset: Ability to manage and resolve complex challenges with little to no established playbooks using creative and proven strategic thinking to drive solutions.

• Cross-Functional Leadership: Demonstrated ability to work effectively across diverse teams (Engineering Product Operations Partnerships etc.).

• Communication Skills: Exceptional verbal and written communication skills. Comfort in presenting Metrics and Quality approaches to senior leadership and external stakeholders.

• Risk Management: Proven track record of identifying managing and mitigating risks in large complex programs.

• Adaptability: Comfortable with ambiguity and able to thrive in a fast-moving constantly evolving environment.

• Travel: Willing to travel domestically and internationally up to 20%

• Bachelors or Masters degree in Engineering (Mechanical Electrical Systems or related field)

• 8 years of experience in product quality manufacturing quality or reliability engineeringpreferably in component level system hardware robotics and/or autonomous systems

• Proven experience across NPI phases (EVT DVT PVT ramp sustaining)

• Deep expertise in quality systems: FMEA SPC CAPA 8D Six Sigma methodologies

• Hands-on experience overseeing quality processes enabling checks and balances developing supplier with quality first mindset

• Strong background in reliability engineering and failure analysis

• Experience with fleet-based or deployed systems is highly preferred

If you thrive in dynamic environments love solving complex challenges and want to make an impact with cutting-edge technology wed love to hear from you!

You spend your day turning messy cross-functional problems into structured insights and scalable fixesso the product works reliably at scale.

You usually start by reviewing dashboards and overnight reports:

• Fleet health metrics (uptime failure rates MTBF/MTTR)

• Manufacturing yield and defect paretos from the previous build

• Any critical field escalations or production line stops

If something is offsay a spike in failures in a subsystemyoull quickly prioritize it for deeper investigation.

From there you jump into a cross-functional stand-up with hardware software manufacturing and operations:

• Align on top quality risks across EVT/DVT/PVT or production builds

• Review open issues owners and timelines

• Decide where escalation or additional resources are needed

Youre setting the tone: what matters today and what cannot slip.

This is where you spend focused time on root cause analysis.

Example scenarios:

• A recurring field failure in the robotic fleet youre reviewing logs diagnostic data and failure modes with the firmware and systems teams

• A yield drop at a contract manufacturer digging into process changes supplier variation or test coverage gaps

• A reliability test failure working with engineering to understand whether its a design limitation or test artifact

Youre not just asking what failedyoure pushing toward:

• Root cause clarity (not symptoms)

• Containment actions (what do we do now)

• Permanent fixes (design process or supplier changes)

Depending on the phase of the program this block varies:

• During NPI builds (EVT/DVT/PVT):
  Youre on the line (physically or virtually) reviewing:

  • First pass yield

  • Assembly issues (DFA gaps)

  • Test coverage and escapes

• During production:

  • Reviewing IQC/IPQC/OQC trends

  • Syncing with supplier quality teams on incoming defects

  • Auditing process controls and corrective actions

• For fleet operations:

  • Meeting with field ops on triage trends

  • Reviewing top downtime drivers

  • Prioritizing fixes that impact uptime and serviceability

This is where you zoom out from individual issues to system-level improvements.

You might be:

• Building or refining quality dashboards and KPIs

• Defining new quality gates for upcoming builds or releases

• Improving diagnostic frameworks so failures are easier to detect and classify

• Working on automated test strategies (production or validation)

This is also where AI and tooling come in:

• Setting up automated anomaly detection on fleet or manufacturing data

• Streamlining how issues are categorized and routed

• Reducing manual triage work through smarter workflows

The goal: make the system smarter so the same problems dont repeat.

Youll often close the day in decision-making forums:

• Design reviews (pushing for DFM/DFA improvements)

• Quality reviews with leadership (status risks mitigation plans)

• Supplier calls for escalations or performance management

This is where you influence:

• Whether a build proceeds or is gated

• Whether a design is ready for the next phase

• Where the team invests time and resources

Before wrapping up you:

• Reassess top risks across product manufacturing and fleet

• Ensure owners and timelines are clear for critical issues

• Prepare concise updates for leadership (whats broken whats improving whats at risk)

• Youre one of the few roles that sees the full picturedesign factory field

• You operate at both microscopic level (root cause) and system level (process metrics)

• You constantly balance speed vs. quality in a fast-moving hardware environment

• No two days are the samepriorities shift based on real-world data

Our roles are often flexible. If you dont fit all the criteria or are in another location (especially one where we have an office like SF or NY) please apply anyway! Wed love to consider you.

Bedrock Robotics is an Equal Opportunity Employer

Were committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race color religion sex sexual orientation gender identity national origin ancestry age disability veteran status genetic information or any other protected characteristic.

Reasonable Accommodations

We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process please let your recruiter know so we can support you.

Required Experience:

Senior IC